Development of a system for the collection, analysis and utilisation of product authenticity data (FoodAuthent)

09/2016-09/2019

This third-party funded project is conducted in the framework of the BfR research programme on authenticity testing of food and feed.

BMEL support programme: Promotion of innovation

BLE grant number: 2816502914

Project homepage: www.foodauthent.de/

Project description:

One of the difficulties in detecting food fraud is the fact that in most cases, only the substance that is being looked for can be found. A food is therefore tested for various falsifications that are already known, but unknown additives and adulterations can be overlooked using this approach. The goal of more recent research work is therefore the development of so-called non-targeted analytical methods which also make it  possible in principle to identify unknown adulterations, especially unexpected additives.

In a non-targeted analysis, the ingredients of a food sample, i.e. its "chemical fingerprint", are described through the combination of spectroscopy or spectrometry and multivariate data analysis. By determining the natural variation through the analysis of unadulterated, authentic samples of a specified food, a reference database with chemical fingerprints is built up against which a new sample is tested. Through comparison with the authentic spectrum of each anticipated product, the identification of many different deviations is possible, e. g. the identification of products which were accidentally or intentionally adulterated.

In addition to the analytical prerequisites, which include above all the comparability of the results of measurements in different laboratories, the joint utilisation of data and databases of control institutions (public and private sector) also poses a great challenge when establishing these approaches in routine analysis.

For the first time, the integration of accessible fingerprinting databases which is to be realised in the project, with standardised protocols for sample testing, validated statistical data analysis methods, uniform data exchange formats and a connection to product databases operated by the private sector, provides the opportunity of making effective use of the potential concealed in fingerprinting analysis. Jointly used, cloud-based food fingerprinting databases are being created and open, reproducible pattern recognition and data analysis methods developed. This also includes link-ups to IT systems containing batch-specific product information.

Through the interdisciplinary cooperation of experts from the fields of food analysis, food trading, software development, data mining and standardisation, the prerequisites are also being created for ensuring that analytical fingerprinting methods will be able to make a significant contribution towards the safety and transparency of the flows of food products all the way through to the consumer in future.

BfR parts of the project:

The project is divided into part A (fingerprinting analysis & data mining) and B (system concept & end user services), which are divided further into nine work packages (WP). The BfR is coordinator of part A and is involved in all WP.

Project partners:

  • University of Konstanz, Germany
  • Lablicate GmbH, Germany
  • Eurofins Analytik GmbH, Germany
  • benelog GmbH & Co. KG, Germany
  • GS1 Germany GmbH, Germany


There are no documents on your notepad

There are no documents in your cart

Cookie Notice

This site only uses cookies to offer you a better browsing experience. Find out more on how we use cookies in our Data Protection Declaration.